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Intro to AI for GLAM

This lesson aims to empower GLAM (Galleries, Libraries, Archives, and Museums) staff by providing the foundation to support, participate in and begin to undertake in their own right, machine learning-based research and projects with heritage collections.

After attending, learners will be able to:

Prerequisites

None

Schedule

Setup Download files required for the lesson
00:00 1. Welcome Who is this lesson for?
What will we be covering in this lesson?
What will we not be covering in this lesson?
00:05 2. Artificial Intelligence (AI) and Machine Learning (ML) in a nutshell What is a brief history of the field of (AI) and Machine Learning (ML)?
What do we mean by Artificial Intelligence and Machine Learning? How are they defined?
00:05 3. Machine Learning Modelling Concepts What are models and algorithms?
What factors should we consider when choosing a machine learning model?
00:05 4. What is Machine Learning good at? What are the tasks where machine learning excels?
00:45 5. Understanding and managing bias What are common types of bias and their effect in machine learning?
At what points can bias enter the machine learning pipeline?
Can we manage bias? Some lessons from GLAM
00:45 6. Applying Machine Learning What are the key steps involved in a machine learning project?
What skills and people should be involved in a machine learning project?
How can machine learning models predictions be utilised by an organization?
00:45 7. The Machine Learning ecosystem FIXME
00:45 Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.